The five-step process
Plain English description
You describe who you are looking for in natural language. No filters, dropdowns, or field mapping. Examples: "Early-stage SaaS founders who write publicly about product-led growth and have raised a seed round in the last 18 months." Or: "Heads of RevOps at Series A B2B companies who post about their sales stack." The only input is a sentence or two about the person you need.
ICP refinement through follow-up questions
WhoEngine asks a small number of intelligent follow-up questions to sharpen your Ideal Customer Profile. These questions target the dimensions that matter most for your search: geography, company stage, specific signals of intent, and any constraints that would disqualify an otherwise strong match. Sharpening the ICP at this step meaningfully improves the precision of what comes back.
Live public web search
WhoEngine searches the public web in real time using neural search. It does not query a static contact database. Results reflect current public information: what people have written this year, where they have spoken recently, what companies they are at today. Three parallel search strategies run simultaneously to maximize coverage across different signal types.
Multi-layer signal analysis
For each candidate found, WhoEngine reads and analyzes the actual page text from their public presence. It extracts writing, talks, affiliations, credibility signals, and behavioral indicators. It then scores each person on how well those signals match the ICP, with a specific cited reason explaining the match. Candidates who do not meet a minimum quality threshold are filtered out before the results are returned.
Ranked shortlist with cited reasons
WhoEngine returns approximately 25 matches ranked by fit. Each match includes name, role, company, location, a numeric match score, and a cited reason that explains specifically why this person fits the description. The reason references actual public signal: what they wrote, where they spoke, what their company does. Paid plans also include full contact details and an AI-drafted outreach message personalized to each match.
Signal categories
WhoEngine analyzes 8 categories of public signal for each candidate. The categories analyzed depend on search mode: B2B searches focus on professional signals, B2C searches extend to personal profile and lifestyle signals.
- Public writing
Newsletters, blog posts, LinkedIn long-form articles, personal websites, Substack publications, and Medium essays. Writing is the highest-signal category because it reveals what someone thinks about, cares about, and knows, in their own words.
- Conference talks and podcast appearances
Keynote sessions, panel discussions, podcast episodes, and recorded interviews. Speaking engagements signal credibility, domain authority, and the specific problems a person is publicly associated with.
- Open source contributions and technical projects
GitHub repositories, open source project contributions, technical specifications, and public demos. For technical roles, this category often reveals more about depth and focus than any profile field.
- Professional affiliations and board memberships
Named board roles, advisory positions, investor portfolios, professional association memberships, and working group participation. Affiliations reveal relationships, commitments, and organizational alignment.
- Media coverage and third-party citations
Press mentions in trade and general publications, analyst reports that name an individual, and awards or rankings from credible third parties. Third-party coverage is a strong credibility signal because it represents external validation.
- Peer recognition signals
Who cites, recommends, or refers to this person in their own public writing and talks. Co-authorship and co-speaking patterns. Peer signal is particularly valuable for identifying genuine authority versus self-reported expertise.
- Financial capacity indicators
Publicly available indicators of budget authority, company funding stage, role seniority, and deal history for investors. WhoEngine derives a capacity tier from cited public sources. No paid data sources are used.
- Personal profile signals
Education, homeownership, family, vehicle, pets, lifestyle, hobbies, collections, entertainment preferences, travel, and civic affiliations publicly shared across social profiles and personal sites. Used primarily in consumer-facing searches to build a richer picture of the individual.
Grounding and accuracy
Every signal extracted by WhoEngine is grounded in a source URL from the actual page where it was found. The system uses three independent enforcement layers to prevent fabricated or inferred data from reaching a lead record.
- Temperature zero inference
All extraction calls run at temperature zero. This means the AI model reads and reports what it finds rather than completing or embellishing with plausible-sounding content.
- Strict prompt rules
The extraction prompt requires the target person's name and the specific fact to appear on the same page, descriptions to be direct quotes or minimal paraphrases within 20 words, and omission of any fact where there is any name ambiguity.
- Source URL allowlist validation
After the model responds, every signal's source URL is checked against the set of URLs actually fetched in that request. Any URL the model invented, shortened, or modified is dropped before it can reach a lead record. Dropped signals are logged as warnings.
Technical foundation
WhoEngine is built on large language models for ICP interpretation, signal extraction, match scoring, and reason generation. Real-time web retrieval uses Exa, a neural search API designed for semantic relevance rather than keyword matching.
The pipeline runs multiple parallel search strategies for each query to maximize signal coverage across different parts of the public web. For enrichment, additional parallel searches target specific signal groups (credentials, lifestyle, media presence, financial and community) independently, then merge and deduplicate results before they reach the output.
WhoEngine does not maintain a proprietary contact database. There is no static dataset to go stale. Every search is a live operation, which means the results reflect what is publicly available at the time of the search.
Frequently asked questions
- Does WhoEngine use a contact database?
- No. WhoEngine does not maintain a proprietary contact database. Every search queries the live public web, which means results reflect current public information rather than data that may be months or years out of date.
- How accurate are the contact details?
- Contact details are extracted from public sources found during the search: personal websites, social profiles, professional pages, and public directories. WhoEngine only includes a contact detail if it literally appears in the source text. Nothing is inferred or guessed. Accuracy depends on how current and complete the person's public presence is.
- How long does a search take?
- Search time varies with the complexity of the ICP, the number of follow up questions asked, and the breadth of public signal available for each candidate. You review a ranked shortlist with cited reasons when the search finishes.
- What is an Ideal Customer Profile and why does it matter?
- An Ideal Customer Profile (ICP) is a precise description of the type of person most likely to buy from you, join your team, or align with your goals. The quality of the ICP directly determines the precision of the results. WhoEngine's follow-up questions are designed to sharpen the ICP so the search returns fewer but better matches.
- Can WhoEngine search for both B2B and B2C targets?
- Yes. WhoEngine has a B2B mode for finding professionals by their work, role, and public contributions, and a B2C mode for finding individuals by their personal profile, life events, and consumer signals. Both modes use the same plain English input and ranked output format.
- How is WhoEngine different from LinkedIn Sales Navigator?
- LinkedIn Sales Navigator filters LinkedIn's profile database using demographic attributes such as job title, company size, and seniority level. It does not read what people actually write, say, or contribute. WhoEngine searches the entire public web, reads behavioral signals, and ranks by signal quality rather than demographic match. WhoEngine returns a curated shortlist with a cited reason for each match.
See it in action
Run a free search now. No account required. Describe who you need in plain English and see a ranked preview with the reason each person fits.